def get_loader(*args, **kwargs):
dataset = data.ToyTask(*args, **kwargs)
loader = torch.utils.data.DataLoader(
dataset,
batch_size=1024,
num_workers=8,
pin_memory=True,
)
return loader
def visualize_dataset():
params = [0.1, 0.2, 0.3, 0.4, 0.5, None]
plt.figure(figsize=(11.5, 4), dpi=200)
for n, length in enumerate(params):
task = data.ToyTask(length=length,)
weights, boxes, true_num = next(iter(task))
print(true_num, len(weights))
true_fig = plt.subplot(2, len(params), n*2+1, aspect='equal')
data_fig = plt.subplot(2, len(params), n*2+2, aspect='equal')
for index in range(boxes.size()[1]):
box = boxes[:, index]
x = box[0]
y = box[1]
w = box[2] - box[0]
h = box[3] - box[1]
# Given images
# As for color, "1" represents true, "0" represents false.
# Therefore, the red rectangle represents true object.
# the blue rectangle represents false object.
data_fig.add_patch(patches.Rectangle((x, y), width=w, height=h, alpha=0.5,
linewidth=0, color=cm(float(weights[index]))))
# In fact
if index < true_num:
true_fig.add_patch(patches.Rectangle((x, y), width=w, height=h, alpha=0.5, linewidth=0,
color=cm(float(1))))
else:
true_fig.add_patch(patches.Rectangle((x, y), width=w, height=h, alpha=0.5, linewidth=0,
color=cm(float(0))))
true_fig.axes.get_xaxis().set_visible(False)
data_fig.axes.get_xaxis().set_visible(False)
true_fig.axes.get_yaxis().set_major_locator(plt.NullLocator())
data_fig.axes.get_yaxis().set_visible(False)
true_fig.set_title('Ground truth: {}'.format(true_num))
data_fig.set_title('Given Data')
if length:
true_fig.set_ylabel('$length = {}$'.format(length))
else:
true_fig.set_ylabel('$length=random$')
plt.show()
random.seed(int(2 * q) + 16)
cm = plt.cm.coolwarm
params = [
(0.05, q),
(0.1, q),
(0.2, q),
(0.3, q),
(0.4, q),
(0.5, q),
]
n = 0
plt.figure(figsize=(4, 11.5), dpi=200)
for coord, noise in params:
dataset = data.ToyTask(10, coord, noise)
a, b, c = next(iter(dataset))
ax_true = plt.subplot(len(params), 2, n + 1, aspect='equal')
ax_data = plt.subplot(len(params), 2, n + 2, aspect='equal')
for i, (weight, box) in enumerate(zip(a, b)):
x = box[0]
y = box[1]
w = box[2] - box[0]
h = box[3] - box[1]
config = {
'alpha': 0.3,
'linewidth': 0,
}
ax_true.add_patch(